/**
 * Copyright 2012 Brigham Young University
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package edu.byu.nlp.cluster.mom;

import org.apache.commons.math3.random.RandomGenerator;

import edu.byu.nlp.stats.DirichletDistribution;
import edu.byu.nlp.stats.RandomGenerators;

class SampleAssigner implements Assigner {

	private final RandomGenerator rnd;
	
	public SampleAssigner(RandomGenerator rnd) {
		this.rnd = rnd;
	}
	
	/** {@inheritDoc} */
	@Override
	public void assignThetaInPlace(double[] alphaStar) {
		DirichletDistribution.logSampleToSelf(alphaStar, rnd);
	}

	/** {@inheritDoc} */
	@Override
	public void assignPhiInPlace(double[][] betaStar) {
		DirichletDistribution.logSampleToSelf(betaStar, rnd);
	}

	/** {@inheritDoc} */
	@Override
	public int assignY(double[] completeConditional) {
		return RandomGenerators.nextIntUnnormalizedLogProbs(rnd, completeConditional);
	}
	
}